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Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework

Engström, Kerstin LU ; Olin, Stefan LU ; Rounsevell, Mark D A; Brogaard, Sara LU ; Van Vuuren, Detlef P.; Alexander, Peter; Murray-Rust, Dave and Arneth, Almut LU (2016) In Earth System Dynamics 7(4). p.893-915
Abstract

We present a modelling framework to simulate probabilistic futures of global cropland areas that are conditional on the SSP (shared socio-economic pathway) scenarios. Simulations are based on the Parsimonious Land Use Model (PLUM) linked with the global dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) using socio-economic data from the SSPs and climate data from the RCPs (representative concentration pathways). The simulated range of global cropland is 893-2380 Mha in 2100 (± 1 standard deviation), with the main uncertainties arising from differences in the socio-economic conditions prescribed by the SSP scenarios and the assumptions that underpin the translation of qualitative SSP storylines into... (More)

We present a modelling framework to simulate probabilistic futures of global cropland areas that are conditional on the SSP (shared socio-economic pathway) scenarios. Simulations are based on the Parsimonious Land Use Model (PLUM) linked with the global dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) using socio-economic data from the SSPs and climate data from the RCPs (representative concentration pathways). The simulated range of global cropland is 893-2380 Mha in 2100 (± 1 standard deviation), with the main uncertainties arising from differences in the socio-economic conditions prescribed by the SSP scenarios and the assumptions that underpin the translation of qualitative SSP storylines into quantitative model input parameters. Uncertainties in the assumptions for population growth, technological change and cropland degradation were found to be the most important for global cropland, while uncertainty in food consumption had less influence on the results. The uncertainties arising from climate variability and the differences between climate change scenarios do not strongly affect the range of global cropland futures. Some overlap occurred across all of the conditional probabilistic futures, except for those based on SSP3. We conclude that completely different socio-economic and climate change futures, although sharing low to medium population development, can result in very similar cropland areas on the aggregated global scale.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Earth System Dynamics
volume
7
issue
4
pages
23 pages
publisher
Copernicus Gesellschaft Mbh
external identifiers
  • scopus:84997503471
  • wos:000388188900001
ISSN
2190-4979
DOI
10.5194/esd-7-893-2016
language
English
LU publication?
yes
id
4ef190fb-0968-4271-873d-1ef42c3a1cca
date added to LUP
2016-12-12 10:01:41
date last changed
2017-09-24 05:04:36
@article{4ef190fb-0968-4271-873d-1ef42c3a1cca,
  abstract     = {<p>We present a modelling framework to simulate probabilistic futures of global cropland areas that are conditional on the SSP (shared socio-economic pathway) scenarios. Simulations are based on the Parsimonious Land Use Model (PLUM) linked with the global dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) using socio-economic data from the SSPs and climate data from the RCPs (representative concentration pathways). The simulated range of global cropland is 893-2380 Mha in 2100 (± 1 standard deviation), with the main uncertainties arising from differences in the socio-economic conditions prescribed by the SSP scenarios and the assumptions that underpin the translation of qualitative SSP storylines into quantitative model input parameters. Uncertainties in the assumptions for population growth, technological change and cropland degradation were found to be the most important for global cropland, while uncertainty in food consumption had less influence on the results. The uncertainties arising from climate variability and the differences between climate change scenarios do not strongly affect the range of global cropland futures. Some overlap occurred across all of the conditional probabilistic futures, except for those based on SSP3. We conclude that completely different socio-economic and climate change futures, although sharing low to medium population development, can result in very similar cropland areas on the aggregated global scale.</p>},
  author       = {Engström, Kerstin and Olin, Stefan and Rounsevell, Mark D A and Brogaard, Sara and Van Vuuren, Detlef P. and Alexander, Peter and Murray-Rust, Dave and Arneth, Almut},
  issn         = {2190-4979},
  language     = {eng},
  month        = {11},
  number       = {4},
  pages        = {893--915},
  publisher    = {Copernicus Gesellschaft Mbh},
  series       = {Earth System Dynamics},
  title        = {Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework},
  url          = {http://dx.doi.org/10.5194/esd-7-893-2016},
  volume       = {7},
  year         = {2016},
}